Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free ‘Owl’ and ‘Lizard’: patterns of head pose and eye pose in driver gaze classification

Loading full text...

Full text loading...

/deliver/fulltext/iet-cvi/10/4/IET-CVI.2015.0296.html;jsessionid=c1fiifpfi7sc4.x-iet-live-01?itemId=%2fcontent%2fjournals%2f10.1049%2fiet-cvi.2015.0296&mimeType=html&fmt=ahah

References

    1. 1)
      • 8. Victor, T., Dozza, M., Bärgman, J., et al: ‘Analysis of naturalistic driving study data: safer glances, driver inattention, and crash risk’, 2014.
    2. 2)
      • 9. Lee, J., Muñoz, M., Fridman, L., et al: ‘Investigating drivers’ head and glance correspondence’, Transp. Res. F, Traffic Psychol. Behav., 2016, In press.
    3. 3)
      • 10. Gaur, R.P., Jariwala, K.N.: ‘A survey on methods and models of eye tracking, head pose and gaze estimation’, J. Emerg. Technol. Innov. Res., JETIR, 2014, 1, (5), (October-2014), pp. 265273.
    4. 4)
      • 18. King, D.E.: ‘Dlib-ml: a machine learning toolkit’, J. Mach. Learn. Res., 2009, 10, pp. 17551758.
    5. 5)
      • 14. Al-Rahayfeh, A., Faezipour, M.: ‘Eye tracking and head movement detection: a state-of-art survey’, IEEE J. Translational Eng. Health Med., 2013, 1, pp. 2 100 2122 100 212.
    6. 6)
      • 20. Wagner, A., Wright, J., Ganesh, A., et al: ‘Toward a practical face recognition system: robust alignment and illumination by sparse representation’, IEEE Trans. Pattern Anal. Mach. Intell., 2012, 34, (2), pp. 372386.
    7. 7)
      • 5. D. F.-T. W. Group et al.: ‘Statement of principles, criteria and verification procedures on driver interactions with advanced in-vehicle information and communication systems’. Alliance of Automotive Manufacturers, 2006.
    8. 8)
      • 3. Senders, J.W., Kristofferson, A., Levison, W., et al: ‘The attentional demand of automobile driving’, Highw. Res. Rec., 1967, 195, pp. 1533.
    9. 9)
      • 22. Schweighofer, G., Pinz, A.: ‘Globally optimal o (n) solution to the pnp problem for general camera models’. British Machine Vision Conf. (BMVC), 2008, pp. 110.
    10. 10)
      • 1. Klauer, S.G., Dingus, T.A., Neale, V.L., et al: ‘The impact of driver inattention on near-crash/crash risk: an analysis using the 100-car naturalistic driving study data’. Technical Report, National Highway Traffic Safety Administration, 2006.
    11. 11)
      • 11. Sireesha, M., Vijaya, P., Chellamma, K.: ‘A survey on gaze estimation techniques’. Proc. Int. Conf. on VLSI, Communication, Advanced Devices, Signals & Systems and Networking (VCASAN-2013), 2013, pp. 353361.
    12. 12)
      • 7. Fridman, L., Langhans, P., Lee, J., et al: ‘Driver gaze region estimation without using eye movement’, IEEE Intell. Syst., 2016, in press.
    13. 13)
      • 13. Murphy-Chutorian, E., Trivedi, M.M.: ‘Head pose estimation in computer vision: a survey’, IEEE Trans. Pattern Anal. Mach. Intell., 2009, 31, (4), pp. 607626.
    14. 14)
      • 23. Bradski, G., Kaehler, A.: ‘Learning OpenCV: computer vision with the OpenCV library’ (O'Reilly Media, Inc., 2008).
    15. 15)
      • 21. Sagonas, C., Tzimiropoulos, G., Zafeiriou, S., et al: ‘300 faces in-the-wild challenge: the first facial landmark localization challenge’. 2013 IEEE Int. Conf. on Computer Vision Workshops (ICCVW), 2013, pp. 397403.
    16. 16)
      • 12. Kazemi, V., Sullivan, J.: ‘One millisecond face alignment with an ensemble of regression trees’. 2014 IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2014, pp. 18671874.
    17. 17)
      • 17. Smith, D., Chang, J., Glassco, R., et al: ‘Methodology for capturing driver eye glance behavior during in-vehicle secondary tasks’, Transp. Res. Rec.: J. Transp. Res. Board, 2005, 1937, pp. 6165.
    18. 18)
      • 2. Liang, Y., Lee, J.D., Yekhshatyan, L.: ‘How dangerous is looking away from the road? Algorithms predict crash risk from glance patterns in naturalistic driving’, Hum. Factors J. Hum. Factors Ergon. Soc., 2012, 54, (6), pp. 11041116.
    19. 19)
      • 25. Batista, G.E., Prati, R.C., Monard, M.C.: ‘A study of the behavior of several methods for balancing machine learning training data’, ACM Sigkdd Explorations Newsl., 2004, 6, (1), pp. 2029.
    20. 20)
      • 6. Coughlin, J.F., Reimer, B., Mehler, B.: ‘Monitoring, managing, and motivating driver safety and well-being’, IEEE Pervasive Comput., 2011, 10, (3), pp. 1421.
    21. 21)
      • 4. N.H.T.S. Administration et al.: ‘Visual-manual NHTSA driver distraction guidelines for in-vehicle electronic devices’ (National Highway Traffic Safety Administration (NHTSA), Department of Transportation (DOT), Washington, DC, 2012).
    22. 22)
      • 15. Asadifard, M., Shanbezadeh, J.: ‘Automatic adaptive center of pupil detection using face detection and CDF analysis’. Proc. Int. Multi Conf. of Engineers and Computer Scientists, 2010, vol. 1, p. 3.
    23. 23)
      • 19. Lienhart, R., Maydt, J.: ‘An extended set of Haar-like features for rapid object detection’. Proc. 2002 Int. Conf. on Image Processing 2002, 2002, vol. 1, p. I900.
    24. 24)
      • 16. Mehler, B., Kidd, D., Reimer, B., et al: ‘Multi-modal assessment of on-road demand of voice and manual phone calling and voice navigation entry across two embedded vehicle systems’, Ergonomics, 2015, pp. 124.
    25. 25)
      • 24. Pedregosa, F., Varoquaux, G., Gramfort, A., et al: ‘Scikit-learn: machine learning in Python’, J. Mach. Learn. Res., 2011, 12, pp. 28252830.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cvi.2015.0296
Loading

Related content

content/journals/10.1049/iet-cvi.2015.0296
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address